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From | Maarten buis <maartenbuis@yahoo.co.uk> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: y-standardisation in logistic multilevel models with gllamm |
Date | Wed, 16 Mar 2011 08:40:52 +0000 (GMT) |
--- On Wed, 16/3/11, Tina Schmid wrote: > When comparing coefficient X1 in binary logistic regression > across models (same sample, but different covariates), y > standardization of the coefficient is required (see for > example Mood 2010, Logistic Regression: Why we cannot do > what we think we can do, and what we can do about it, ESR, > 26 (1), 67-82). So far, so good. Unfortunately, that is not quite true (and it is also not quite the conclusion from the article that you cite). Standardization will only help when you are interested in the standardized latent dependent variable, which is almost never the case. More often you are interested in either the probabilty or odds, and these change in fundamental ways when you add or remove variables. Probabilties or odds contain both information on the central tendency and on uncertainty. The uncertainty comes from variables not in your model. So the definition of our dependent variable depends on the variables we choose to include in our model, and when we change those variables then we are also changing the definition of our dependent varianble, making it impossible to directly compare coefficients. Standardization won't help, as that is working on a different scale. One possibility is to choose one of the models as the definition of probability of interest and transform the remaining model to that scale. This is what I did in: Maarten L. Buis (2010) "Direct and indirect effects in a logit model" The Stata Journal,10(1): 11-29. Botom line is that there is no easy solution to this problem. Hope this is not too depressing, Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/